Reports on the Application of Text and Data Mining Tools

Data mining tools from Insightful Corporation were applied to JetBlue’s flight operations quality assurance (FOQA) digital flight data to provide guidance on tools which may be useful in enhancing the current analysis of airline digital fight data. The project found that a number of data mining techniques and associated graphical outputs show promise in increasing efficiencies in current FOQA analysis methods, improving data quality monitoring, and identifying “new” potential safety issues by looking across multiple attributes in the source data. December 2004.

This technology demonstration applied text mining routines by Provalis Research Corporation to text-intensive safety reports at JetBlue Airways. Flight safety staff at JetBlue Airways believe these analysis routines may be useful in enhancing the current analysis of airline safety reports. February 2005.

A data mining tool produced by Smiths Aerospace specifically for aerospace applications was applied to two British Airways (BA) flight data monitoring databases, flight data events and flight data measurements. BA found that the analysis delivered useful and intriguing results, many of which were already known to BA and validated the tool, plus some “second level” results which had not been previously unearthed by existing analysis techniques. December 2004.

This project examined how text mining techniques and methods can analyze flight safety reports to reveal patterns that may not be known or easily found. IATA analysts believe these capabilities may be useful in enhancing the analysis of airline safety reports on a global scale. October 2004.

This report describes a joint proof-of-concept project by Southwest Airlines and Megaputer Intelligence to facilitate and promote the use of automated data and text mining tools in the aviation safety community. January 2004.

This report describes the application of the MITRE Corporation’s Aviation Safety Data Mining Workbench to American Airlines’ Aviation Safety Action Program (ASAP) data, to demonstrate the usefulness of data and text mining tools in the analysis of aviation safety data. January 2004.